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---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut_marriage_sm_560-140_aug_002
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# donut_marriage_sm_560-140_aug_002
This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0472
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3237 | 1.0 | 280 | 0.2879 |
| 0.3617 | 2.0 | 560 | 0.1548 |
| 0.1783 | 3.0 | 840 | 0.1054 |
| 0.0673 | 4.0 | 1120 | 0.0931 |
| 0.0738 | 5.0 | 1400 | 0.0890 |
| 0.0333 | 6.0 | 1680 | 0.0780 |
| 0.018 | 7.0 | 1960 | 0.0740 |
| 0.0606 | 8.0 | 2240 | 0.0681 |
| 0.0148 | 9.0 | 2520 | 0.0637 |
| 0.015 | 10.0 | 2800 | 0.0589 |
| 0.0074 | 11.0 | 3080 | 0.0576 |
| 0.0003 | 12.0 | 3360 | 0.0543 |
| 0.0277 | 13.0 | 3640 | 0.0561 |
| 0.0067 | 14.0 | 3920 | 0.0571 |
| 0.0003 | 15.0 | 4200 | 0.0592 |
| 0.0005 | 16.0 | 4480 | 0.0541 |
| 0.0025 | 17.0 | 4760 | 0.0563 |
| 0.0032 | 18.0 | 5040 | 0.0503 |
| 0.0109 | 19.0 | 5320 | 0.0498 |
| 0.0003 | 20.0 | 5600 | 0.0501 |
| 0.0025 | 21.0 | 5880 | 0.0504 |
| 0.0007 | 22.0 | 6160 | 0.0480 |
| 0.0002 | 23.0 | 6440 | 0.0476 |
| 0.0029 | 24.0 | 6720 | 0.0474 |
| 0.0003 | 25.0 | 7000 | 0.0472 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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